Files

Upload a health document to the Subject’s store. Mirobody saves the original first, then in the background extracts its readable text — OCR for PDFs and images, a straight conversion for spreadsheets and text files — and runs the same standardization pipeline as POST /v1/standardize over it, so an uploaded lab report also lands as standardized records. The agent reads both when it answers.

Note

Uploads are capped at 100 MB per file — larger requests return 413. For big exports or realtime streams, use the WebSocket upload path.

Upload a file

POST /v1/files
Authorization: Bearer mb_live_*
Content-Type:  multipart/form-data

Field	Description
file	The document (PDF / image / Excel / CSV).
user	Subject the file belongs to. Optional — omitting it falls back to your account’s default Subject, so always pass it for per-end-user isolation.
retention	Optional here (unlike POST /v1/data, where it’s required). Same values as Data retention.
session_id	Optional; scopes retention=session uploads to a session.

curl https://api.mirobody.ai/v1/files \
  -H "Authorization: Bearer $MIROBODY_API_KEY" \
  -F "user=alice" \
  -F "file=@checkup_2026.pdf"

Response:

{
  "object": "file",
  "id": "AUmIn_R-Ddg.../b/bM--fG29X....pdf",
  "filename": "checkup_2026.pdf",
  "bytes": 20544,
  "status": "processed",
  "created_at": 1782924296,
  "subject": "alice"
}

The file’s identifier is id (a slash-containing key) — use it as {file_key} in the fetch and delete calls below. created_at is epoch seconds.

Note

status: "processed" confirms the original was accepted and stored — its text may still be processing. A GET /v1/files/{file_key} immediately after upload can return an empty extracted_text; retry after a short delay.

An upload makes the document’s text readable by the agent, and Mirobody also pulls the report’s readings out of it — standardized exactly like a POST /v1/data write — and stores them as records. Query them from GET /v1/data without re-entering anything; re-uploading the same file creates no duplicates. Prefer POST /v1/standardize when you’d rather run that extraction yourself and check the readings first. Already have structured records? Send them to POST /v1/data.

List files

GET /v1/files?user=alice
Authorization: Bearer mb_live_*

{
  "object": "list",
  "data": [
    {
      "object": "file",
      "id": "AUmIn_R-Ddg.../b/bM--fG29X....pdf",
      "file_key": "AUmIn_R-Ddg.../b/bM--fG29X....pdf",
      "filename": "checkup_2026.pdf",
      "file_type": "application/pdf",
      "bytes": 20544,
      "created_at": 1782924296
    }
  ],
  "subject": "alice"
}

data holds the files; subject echoes the Subject. Each item exposes both id and file_key (identical values). created_at is epoch seconds, matching the upload response.

Fetch parsed text

GET /v1/files/{file_key}?user=alice
Authorization: Bearer mb_live_*

Returns the extracted text for one file — the same content the agent reads:

{
  "object": "file",
  "id": "AUmIn_R-Ddg.../b/bM--fG29X....pdf",
  "filename": "checkup_2026.pdf",
  "extracted_text": "Annual checkup 2026-06-16\nFasting glucose  97 mg/dL  (ref 70-110)\n...",
  "abstract": "",
  "subject": "alice"
}

extracted_text can be empty while the file’s text is still being processed. abstract may also be empty; it isn’t generated for every file type.

WebSocket upload

For large exports or realtime capture, wss://…/v1/files/stream uploads over one socket with chunking and progress. Auth rides the query string (browsers can’t set WebSocket headers):

wss://api.mirobody.ai/v1/files/stream?key=mb_live_...&user=alice&retention=permanent

Frame sequence (all JSON text frames):

1. Server → you: {"type": "connection_established"} — send nothing before this.
2. You → server: {"type": "upload_start", "messageId": "<batch-id>", "files": [{"filename", "contentType", "size"}]} — one messageId for the whole batch.
3. You → server, per 256 KB chunk: {"type": "upload_chunk", "messageId", "filename", "chunk": "<base64>", "chunkIndex", "totalChunks"}.
4. You → server: {"type": "upload_end", "messageId"} → server replies upload_end_response when every original file has been stored. Its text may still be processing.

Same 100 MB per-file cap, same Subject isolation, and the stored files are identical to a POST /v1/files upload — list them with GET /v1/files.

Delete a file

DELETE /v1/files/{file_key}?user=alice
Authorization: Bearer mb_live_*

Removes the file from the API surface immediately (404 if it isn’t the Subject’s file or is already deleted):

{ "object": "file", "id": "AUmIn_R-Ddg.../b/bM--fG29X....pdf", "deleted": true, "subject": "alice" }

Note

Deleting a file removes the file but not the records auto-extracted from it. To remove those, delete them from the data plane with DELETE /v1/data (by indicator or id), or erase the whole Subject with DELETE /v1/subjects/{user}. (Session-scoped uploads are erased together with their session-scoped records by DELETE /v1/sessions/{id}.)

Time-bounded uploads are also removed automatically at retention expiry — an expired file disappears from every GET /v1/files* read immediately and is then permanently deleted. To erase everything about a Subject at once, use DELETE /v1/subjects/{user} — see Compliance.